Assessment of grassland degradation near Lake Qinghai, West China, using Landsat TM and in situ reflectance spectra data

被引:97
作者
Liu, Y
Zha, Y
Gao, J [1 ]
Ni, S
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
[2] Nanjing Normal Univ, Coll Geog Sci, Nanjing 210097, Peoples R China
[3] Univ Auckland, Sch Geog & Environm Sci, Auckland 1, New Zealand
[4] Nanjing Normal Univ, Coll Geol Sci, Nanjing 210097, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
10.1080/01431160410001680419
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The severity of grassland degradation near Lake Qinghai, West China was assessed from a Landsat Thematic Mapper (TM) image in conjunction with in situ samples of per cent grass cover and proportion (by weight) of unpalatable grasses (PUG) collected over 1 m(2) sampling plots. Spectral reflectance at each sampling plot was measured with a spectrometer and its location determined with a Global Positioning System (GPS) receiver. After radiometric calibration, the TM image was geometrically rectified. Ten vegetation indices were derived from TM bands 3 and 4, and from the spectral reflectance data at wavelengths corresponding most closely to those of TM3 and TM4. Regression analyses showed that NDVI and SAVI are the most reliable indicators of grass cover and PUG, respectively. Significant relationships between TM bands-derived indices and in situ sampled grass parameters were established only after the former had been calibrated with in situ reflectance spectra data. Through the established regression models the TM image was converted into maps of grass cover parameters. These maps were merged to form a degradation map at an accuracy of 91.7%. It was concluded that TM imagery, in conjunction with in situ grass samples and reflectance spectra data, enabled the efficient and accurate assessment of grassland degradation inside the study area.
引用
收藏
页码:4177 / 4189
页数:13
相关论文
共 23 条
[1]   DISTINGUISHING AMONG TALLGRASS PRAIRIE COVER TYPES FROM MEASUREMENTS OF MULTISPECTRAL REFLECTANCE [J].
ASRAR, G ;
WEISER, RL ;
JOHNSON, DE ;
KANEMASU, ET ;
KILLEEN, JM .
REMOTE SENSING OF ENVIRONMENT, 1986, 19 (02) :159-169
[2]  
Bao W., 1998, Grassland of China, P68, DOI [10.3321/j.issn:1673-5021.1998.02.017, DOI 10.3321/J.ISSN:1673-5021.1998.02.017]
[3]  
CHEN GC, 1994, CHINESE J ECOL, V13, P44
[4]   The influence of vegetation index and spatial resolution on a two-date remote sensing-derived relation to C4 species coverage [J].
Davidson, A ;
Csillag, F .
REMOTE SENSING OF ENVIRONMENT, 2001, 75 (01) :138-151
[5]   Applying satellite imagery to triage assessment of ecosystem health [J].
Eve, MD ;
Whitford, WG ;
Havstadt, KM .
ENVIRONMENTAL MONITORING AND ASSESSMENT, 1999, 54 (03) :205-227
[6]   ESTIMATING GRASSLAND BIOMASS AND LEAF-AREA INDEX USING GROUND AND SATELLITE DATA [J].
FRIEDL, MA ;
MICHAELSEN, J ;
DAVIS, FW ;
WALKER, H ;
SCHIMEL, DS .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1994, 15 (07) :1401-1420
[7]  
GONG A., 1999, RESOURCES SCI, V21, P43
[8]   THE USE OF NOAA-AVHRR NDVI DATA TO ASSESS HERBAGE PRODUCTION IN THE ARID RANGELANDS OF CENTRAL AUSTRALIA [J].
HOBBS, TJ .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1995, 16 (07) :1289-1302
[9]  
Li Bo, 1997, Scientia Agricultura Sinica, V30, P1
[10]  
LUDWIG JA, 1986, PATTERN PROCESS DESE, P5